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M. Gutsche, “Surface Velocity Measurements at the Aeolotron by Means of Active Thermography”, Institut für Umweltphysik, Universität Heidelberg, Germany, 2014.
M. Gutsche, “Surface Velocity Measurements at the Aeolotron by Means of Active Thermography”, Institut für Umweltphysik, Universität Heidelberg, Germany, 2014.
B. Güssefeld, Kondermann, D., Schwartz, C., and Klein, R., “Are reflectance field renderings appropriate for optical flow evaluation?”, in International Conference on Image Processing, ICIP 2014, 2014.
B. Güssefeld, Honauer, K., and Kondermann, D., “Creating Feasible Reflectance Data for Synthetic Optical Flow Datasets”, in Advances in Visual Computing - 12th International Symposium, {ISVC} 2016, Las Vegas, NV, USA, December 12-14, 2016, Proceedings, Part {I}, 2016.
V. Gulshan, Rother, C., Criminisi, A., Blake, A., and Zisserman, A., “Geodesic star convexity for interactive image segmentation”, in Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 2010, pp. 3129–3136.
A. Grützmann, “Reconstruction of Moving Surfaces of Revolution from Sparse 3-D Measurements using a Stereo Camera and Structured Light”. IWR, Fakultät für Mathematik und Informatik, Univ.\ Heidelberg, 2009.
K. - H. Grosser, “Entwicklung eines Verfahrens zur optischen Messung der Wellenhöhe von Wasseroberflächenwellen”, Institut für Umweltphysik, Fakultät für Physik und Astronomie, Univ.\ Heidelberg, 1989.
M. Großkinsky, “Synaptic Cleft Prediction on Electron Microsope Images”, Heidelberg University, 2019.
H. Gröning, “Radiometrische Kalibrierung und Charakterisierung von CCD- uund CMOS-Bildsensoren und Monokulares 3D-Tracking in Echtzeit”. IWR, Fakultät für Physik und Astronomie, Univ.\ Heidelberg, 2003.
H. Gröning, “Mehrgitterbewegungssegmentierung und Messungen am grossen Simulationstank zur Bestimmung von Sedimentverlagerungen”, IWR, Fakultät für Physik und Astronomie, Univ.\ Heidelberg, 1996.
M. Griessinger, “Oject Detection with Generic Features: An Application to STED Microscopy”, University of Heidelberg, 2008.
J. Greis, “Semi-automatic analysis of high-information-content neurobiological image data”, University of Heidelberg, 2009.
C. Götz, “Bildverarbeitungsalgorithmen in der Fluoreszenzmikroskopie”, IWR, Fakultät für Physik und Astronomie, Univ.\ Heidelberg, 1999.
J. - M. Gottfried, Nair, R., Meister, S., Garbe, C. S., and Kondermann, D., “Time of flight motion compensation revisited”, in International Conference on Image Processing, ICIP 2014, 2014.
C. Gosch, “Contour Methods for View Point Tracking”. University of Heidelberg, 2009.
C. Gosch, Fundana, K., Heyden, A., and Schnörr, C., “View Point Tracking of Rigid Object Based on Shape Sub-Manifolds”, in Computer Vision – ECCV 2008, 2008, vol. 5302, pp. 251–263.
C. Gosch, Fundana, K., Heyden, A., and Schnörr, C., “View Point Tracking of Rigid Object Based on Shape Sub-Manifolds”, in Computer Vision -- ECCV 2008, 2008, vol. 5302, p. 251--263.PDF icon Technical Report (523.17 KB)
L. Görlitz, “Modern Concepts for Semi-Supervised Learning and Multidimensional Image Processing”. University of Heidelberg, 2007.
L. Görlitz, Singh, M., and Schützbach, P., “Schnelle 3D-Vermessung von Partikeln in Rasterelektronenmiskroskopen mit Hilfe eines Rücksteuerdetektors”. 2007.
L. Görlitz, Menze, B. H., Weber, M. - A., and Kelm, B. Michael, “Semi-Supervised Tumor Detection in MRSI With Discriminative Random Fields”, in Pattern Recognition, 2007, vol. 4713, pp. 224-233.PDF icon Technical Report (872.46 KB)
L. Görlitz, Menze, B. H., Kelm, B. Michael, and Hamprecht, F. A., “Processing Spectral Data”, Surface and Interface Analysis, vol. 41, pp. 636-644, 2009.PDF icon Technical Report (4.17 MB)
L. Görlitz, Hamprecht, F. A., and Staudacher, M., “Allocation of particles to development processes”, Patent, 2009.PDF icon Technical Report (406.7 KB)
L. Görlitz, Hamprecht, F. A., and Staudacher, M., “Detektion von Partikeln in Intensitätsbildern mit Hilfe eines morphologischen Skalenraumes”. Robert-Bosch GmbH, University of Heidelberg, 2005.
D. Gonzalez-Alvarado, Zeilmann, A., and Schnörr, C., “Assignment Flows and Nonlocal PDEs on Graphs”, GCPR, in press. 2021.
B. Goldlücke, Strekalovskiy, E., and Cremers, D., “The natural vectorial total variation which arises from geometric measure theory”, SIAM Journal on Imaging Sciences, 2012.
B. Goldlücke, Strekalovskiy, E., and Cremers, D., “The Natural Vectorial Total Variation which Arises from Geometric Measure Theory”, SIAM Journal on Imaging Sciences, vol. 5, pp. 537-563, 2012.
B. Goldlücke, Aubry, M., Kolev, K., and Cremers, D., “A super-resolution framework for high-accuracy multiview reconstruction”, Int. J. Comp. Vision, vol. 106, p. 172--191, 2014.
B. Goldlücke and Wanner, S., “The Variational Structure of Disparity and Regularization of 4D Light Fields”, in IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2013.
B. Goldlücke, Strekalovskiy, E., and Cremers, D., “Tight convex relaxations for vector-valued labeling”, SIAM Journal on Imaging Sciences, 2013.
B. Glocker, T. Heibel, H., Navab, N., Kohli, P., and Rother, C., “TriangleFlow: Optical flow with triangulation-based higher-order likelihoods”, in Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 2010, vol. 6313 LNCS, pp. 272–285.
J. Gliß, “Entwicklung und Implementierung eines Cavity-Enhanced-Spektrometers am Wind-Wellen-Kanal”, Institut für Umweltphysik, Fakultät für Physik und Astronomie, Univ.\ Heidelberg, 2010.
R. Gleisinger, “Entwurf und Implementation eines objektorientierten Inspektors für multidimensionale wissenschaftliche Daten”, Lehrgebiet praktische Informatik, Fachbereich Informatik Fernuniversität Hagen, 2000.
M. Glas, “Methoden zur sechsdimensionalen Objektlageerkennung aus Tiefenbildern”. IWR, Fakultät für Physik und Astronomie, Univ.\ Heidelberg, 2012.
M. Glas, “Methoden zur sechsdimensionalen Objektlageerkennung aus Tiefenbildern”, vol. Dissertation. IWR, Fakultät für Physik und Astronomie, Univ. Heidelberg, 2012.
J. Giebel, Gavrila, D. M., and Schnörr, C., “A Bayesian Framework for Multi-cue 3D Object Tracking”, in Computer Vision – ECCV 2004, 2004, vol. 3024, pp. 241-252.

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